Associate Director, Deposit Quant Research - Forecasting

PNC; New York (NY); On-site; USD 91,000 - 203,000; Full time

Job summary

PNC is seeking an Associate Director, Deposit Quantitative Research based in New York City, NY or Pittsburgh, PA. The role focuses on developing forecasting models and behavioral analytics for deposit products and balance sheet management.

The candidate will apply econometric and data-driven methods, work with large datasets, and communicate findings to technical and non-technical stakeholders. Master’s is required; PhD preferred.

Qualifications

• Master's degree in Economics, Finance, Econometrics, Statistics, Mathematics, Operations Research, Data Science, or related field.
• 5+ years in empirical research, econometrics, statistical modeling, predictive analytics, or quantitative research.
• Strong programming skills in Python and SQL with experience on large structured datasets.
• Ability to independently formulate research questions, design analytical approaches, and communicate findings to diverse audiences.

Responsibilities

• Utilizes financial analysis, research, and reporting to facilitate business strategy and remediation activities.
• Develops forecasting models and behavioral analytics for deposit products and balance sheet management.
• Presents risk analytics and stress testing materials to senior team members.
• Partners with lines of business to understand balance sheet items and reconciles data quality for review by model risk management and regulators.
• Translates analytical findings into actionable business recommendations.

Skills

Econometrics

Empirical Research

Python

SQL

Communication

Education

Master's degree in a quantitative field

PhD preferred

Tools

Python

SQL

Job description

PNC is seeking an Associate Director, Deposit Quantitative Research based in New York City, NY or Pittsburgh, PA. The role focuses on developing forecasting models and behavioral analytics for deposit products and balance sheet management.

The candidate will apply econometric and data-driven methods, work with large datasets, and communicate findings to technical and non-technical stakeholders. Master’s is required; PhD preferred.